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Methods Mol Biol. 2019;2039:243-262. doi: 10.1007/978-1-4939-9678-0_17.

Atomistic Simulation Tools to Study Protein Self-Aggregation.

Author information

1
Department of Chemical and Physical Sciences, University of Toronto Mississauga, Mississauga, ON, Canada.
2
Department of Physics, University of Toronto, Toronto, ON, Canada.
3
Department of Chemical and Physical Sciences, University of Toronto Mississauga, Mississauga, ON, Canada. sarah.rauscher@utoronto.ca.
4
Department of Physics, University of Toronto, Toronto, ON, Canada. sarah.rauscher@utoronto.ca.
5
Department of Chemistry, University of Toronto, Toronto, ON, Canada. sarah.rauscher@utoronto.ca.

Abstract

Aberrant aggregation of proteins into poorly soluble, toxic structures that accumulate intracellularly or extracellularly leads to a range of disease states including Alzheimer's, Parkinson's, Huntington's, prion diseases, and type II diabetes. Many of the disease-associated amyloidogenic proteins are intrinsically disordered, which makes their experimental investigation challenging due to a limited number of experimental observables to effectively characterize their ensemble of conformations. Molecular dynamics simulations provide dynamic information with atomistic detail, and are increasingly employed to study aggregation processes, offering valuable structural and mechanistic insights. In this chapter, we demonstrate the use of all-atom molecular dynamics simulations to model the self-aggregation of a six-residue amyloidogenic peptide derived from amyloid β, a 39-43 residue-long peptide associated with the pathogenesis of Alzheimer's disease. We provide detailed instructions on how to obtain the initial monomer conformations and build the multichain systems, how to carry out the simulations, and how to analyze the simulation trajectories to investigate the peptide self-aggregation process.

KEYWORDS:

Alzheimer’s disease; Amyloid β; Intrinsically disordered proteins; Molecular dynamics simulations; Protein self-aggregation

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